A new approach to sum-fuzzy rational choice functions

  • Authors:
  • Xiao Luo

  • Affiliations:
  • Department of Economics, National Taiwan University, Taipei 100, Taiwan, ROC

  • Venue:
  • Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
  • Year:
  • 2002

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Abstract

The purpose of this paper is to present a new approach to sum-fuzzy rational choice functions. By making use of the model of perceptrons in neural theory, we establish a sufficient and necessary condition for sum-fuzzy rationality. Moreover, we provide a geometric characterization of sum-fuzzy rationality for single-valued choice functions. Based on the learning rules of perceptrons, we offer an algorithm to find a sum-fuzzy implementation of a choice function and, then, provide a concrete example.